title: Online LS-SVM based multi-step prediction of physiological tremor for surgical robotics.
abstract: Performance of robotics based hand-held surgical devices in real-time is mainly dependent on accurate filtering of physiological tremor. The presence of phase delay in sensors (hardware) and filtering (software) processes affects the cancellation accuracy. This paper focuses on developing an estimation algorithm to improve the estimation accuracy in the presence of phase delay for real-time implementations. Moving window based online training approach for least squares-support vector machines (LSSVM) is employed in this paper for tremor estimation. A study is conducted with tremor data recorded from the subjects to analyze the suitability of proposed approach for both single-step and multi-step prediction.
authors.forename: S
authors.initials: S
authors.lastname: Tatinati
authors.forename: Y
authors.initials: Y
authors.lastname: Wang
authors.forename: G
authors.initials: G
authors.lastname: Shafiq
authors.forename: K C
authors.initials: KC
authors.lastname: Veluvolu
mesh_terms: D000465:Algorithms; D020329:Essential Tremor; D006225:Hand; D006801:Humans; D020407:Internet; D016018:Least-Squares Analysis; D009038:Motion; D009862:Online Systems; D015203:Reproducibility of Results; D065287:Robotic Surgical Procedures; D012371:Robotics / Q000295:instrumentation; D060388:Support Vector Machine; D014202:Tremor / Q000175:diagnosis*